Voice biometrics can be applied to detect fraudulent activity in language proficiency tests to enhance test security—thereby protecting the integrity of tests and ensuring valid test scores. Systems and methods as described herein provide voice biometric capabilities using a trained neural network to generate vectors of speaker metrics that can be compared across vectors associated with a number of known speakers to determine whether a candidate speaker is who they say they are, or to determine that the candidate speaker is not someone who is known to participate in fraudulent behavior. In addition to examination test security, such systems and methods can be used in other voice biometric applications, such as banking and other security identifications.